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Large-scale Models of Esophageal Cancer and Related Research
Sponsor: The First Affiliated Hospital of Henan University of Science and Technology
Summary
The goal of this observational study is to learn about the clinical utility of an artificial intelligence (AI) large language model in patients undergoing screening, diagnosis, treatment, and prognosis assessment for esophageal cancer. The main question it aims to answer is: Does the AI model improve early detection rate, diagnostic accuracy, treatment personalization, and prognostic prediction for esophageal cancer compared to standard care? Participants already receiving routine esophageal cancer management (including endoscopy, imaging, pathology, and clinical follow-up) as part of their regular medical care will have their de-identified data processed by the AI model; researchers will compare model-based recommendations and outcomes with standard care benchmarks over 3 years. Last updated on Oct 31, 2027
Official title: Clinical Application Research of AI-Based Large Models for Early Screening, Diagnosis, Treatment, and Prognosis Assessment of Esophageal Cancer
Key Details
Gender
All
Age Range
18 Years - 90 Years
Study Type
OBSERVATIONAL
Enrollment
12000
Start Date
2026-05-15
Completion Date
2027-10-31
Last Updated
2026-06-11
Healthy Volunteers
No
Conditions
Interventions
Observational study; no assigned intervention. Participants receive routine esophageal cancer management (endoscopy, imaging, pathology, clinical follow-up) as standard care.
Routine esophageal cancer management including endoscopy, imaging, pathology, and clinical follow-up as per standard clinical practice. No additional, experimental, or assigned intervention is administered. The AI large language model processes de-identified data from routine care for comparative analysis against standard care benchmarks over 3 years.
Locations (3)
Anyang Tumor Hospital
Anyang, Henan, China
The First Affiliated Hospital of Henan University of Science & Technology
Luoyang, Henan, China
Nanyang Central Hospital Medical Ethics Committee
Nanyang, Henan, China